在mapper类中，使用HBase API读取表中的多行数据，并将行键（RowKey）作为键，数据作为值传递给Reduce阶段。您可能需要使用scan操作从表中读取多行数据。给出代码

很高兴能回答您的问题！下面是一个示例代码，用于从HBase表中扫描多行数据，并将它们传递到Reduce阶段：

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.hbase.*;
import org.apache.hadoop.hbase.client.*;
import org.apache.hadoop.hbase.mapreduce.TableMapper;
import org.apache.hadoop.hbase.util.Bytes;
import org.apache.hadoop.io.*;
import org.apache.hadoop.mapreduce.Reducer;

import java.io.IOException;

public class MyMapper extends TableMapper<Text, Text> {
    public void map(ImmutableBytesWritable row, Result value, Context context) throws IOException, InterruptedException {
        String rowKey = Bytes.toString(row.get());
        byte[] data = value.getValue(Bytes.toBytes("cf"), Bytes.toBytes("data"));
        String dataValue = Bytes.toString(data);
        context.write(new Text(rowKey), new Text(dataValue));
    }
}

public class MyReducer extends Reducer<Text, Text, Text, Text> {
    public void reduce(Text key, Iterable<Text> values, Context context) throws IOException, InterruptedException {
        for (Text val : values) {
            context.write(key, val);
        }
    }
}

public class HBaseDriver {
    public static void main(String[] args) throws Exception {
        Configuration conf = HBaseConfiguration.create();
        Job job = Job.getInstance(conf, "HBase MapReduce");
        job.setJarByClass(HBaseDriver.class);
        Scan scan = new Scan();
        TableMapReduceUtil.initTableMapperJob("table_name", scan, MyMapper.class, Text.class, Text.class, job);
        job.setReducerClass(MyReducer.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(Text.class);
        job.setNumReduceTasks(1);
        TableMapReduceUtil.initTableReducerJob("output_table", MyReducer.class, job);
        System.exit(job.waitForCompletion(true) ? 0 : 1);
    }
}

这个示例将HBase表中所有行的行键和数据作为键值对传递到Reduce阶段，并将它们写入输出表。您需要替换代码中的“table_name”和“output_table”与您的实际表名。